Orange-Fleshed Sweet Potato (OFSP) is an important crop in Indonesia. Yield potential and genotypic adaptability are important factors in varietal development. The purpose of this study was to estimate the stability of yield and to select the best OFSP genotypes across three agroecosystems in West Java, Indonesia. The field trials used were augmented design with 50 F1 Orange-Fleshed Sweet Potato (OFSP) genotypes as treatment, and seven check varieties as controls. The experiments were conducted in three different agroecosystems in West Java (Sumedang, Bandung, and Karawang). Selection was based on physical characteristics of sweet potato tuber, yield and stability across three environments. Data analysis of the yield characters, yield component, and tuber quality were performed by combined variance analysis. Selected genotypes were analyzed for stability yield using the parametric, non-parametric, Additive Main effects and Multiplicative Interaction (AMMI), AMMI Stability Value (ASV), and Genotype and Genotype by Environment (GGE) biplot models. Results identified the top best ten F1 genotypes namely F1-38 (G1), F1-69 (G2), F1-71 (G3), F1-77 (G4), F1-127 (G5), F1-128 (G6), F1-135 (G7), F1-159 (G8), F1-191 (G9), and F1-226 (G10). Location showed a significant effect on yield. Genotypes F1-069, F1-077, F1-226, F1-038, and F1-128 have the lowest ASR based on non-parametric and parametric stability models and there were identified as the most stable. AMMI analysis identified F1-128, F1-135, F1-038, and F1-069 as the most stable genotypes. F1-38 (G1), F1-69 (G2), F1-128 (G6) were found to be the most stable genotypes based on ASV analysis, while GGE biplot identified F1-38 (G1) and F1-69 (G2) genotypes as the stable genotypes. Other genotypes were considered to as location-specific. Based on AMMI, ASV, and GGE Biplot models, F1-038, and F1-069 were identified as stable genotypes. They produced higher yields than other genotypes. Therefore, the F1-038 and F1-069 genotypes can be potentially recommended as superior varieties for West Java, Indonesia.

There are many local varieties of sweet potatoes which are cultivated and consumed in Indonesia. The food industry which uses sweet potato as the main raw material has been developed in West Java. Demand for orange-fleshed sweet potato is high, but the supply of demand has not been fulfilled. This is because the varieties that are widely cultivated do not meet consumer standards and preferences, so new superior genotypes are needed following demand. Currently, selection of stable and high-yielding genotypes and accordance with consumer and industry preferences is one of the focuses of sweet potato research. Orange-fleshed sweet potato multi locations testing in accordance with consumer and industry preferences, can be used as a basis for consideration in the development program. The purpose of this study were to identify genotype by environment interactions (GEIs) and t select superior genotypes and to estimate yield stability across three locations in West Java, Indonesia. Combined analysis of variance (ANOVA) was used to determine significant differences between each genotype tested in term of yield and to estimated genotype by environment interactions (GEIs). Additive Main Effects and Multiplicative Interaction (AMMI), Genotype Plus Genotype by Environment Interactions (GGE) biplots, and Parametric and non-parametric stability measurements were used to determine yield stability from genotypes tested in all locations (Sumedang Regency, Bandung Regency, Karawang Regency). Data in this article showed that the genotypes, environments, and GEIs had an effect on sweet potato yields, with influences of 35.03%, 18.87%, and 46.01%, respectively. The results in this data also indicate that some new sweet potato genotypes have stable and high yields in three environments in West Java, Indonesia. So they were can be used for development in sweet potato breeding programs.

Genetic studies on yield and yield quality are becoming benchmarks for farmers and industry in selecting and developing varieties. Evaluations that combine various stability statistics can provide more accurate information to select the ideal genotype. This study aims to identify the effect of genotype by environment interactions (GEIs) for yield and yield quality, to select high yield and stable sweet potato genotypes, as well as to select superior genotypes based on yield and yield quality. Three different environments in West Java, Indonesia, were used to test the sweet potato genotypes using a randomized block design that was repeated three times. Highly significant effects of sweet potato genotypes (G), environments (E), and GEIs were observed for yield and yield quality. The Combined ANOVA showed that GEIs effect contributed 54.88% for yield, 40.01% for sweetness, 10.46% for moisture content, 68.80% for tuber diameter, and 72.57% for tuber length from the sum of square. Five most high and stable yield on sweet potato genotypes identified by all measures, includes G4, G6, G7, G31, and G32. Genotype by yield*traits (GYT) selected seven genotypes that have superior in yield and yield quality, they were G7, G15, G4, G20, G6, G31, and G14. Based on stability measurements and GYT biplots, the genotypes G4, G6, G7, and G31 are in both slices. So that the four genotypes have high, stable yields, and have a good combination of traits for yield quality. Our findings can be used for improvement cultivation involving partner companies, partner institutions, and farmers, and the selected genotypes can be release as superior varieties candidate.

Black soybean (Glycine soja (L.) Merril) is one of the potential agricultural commodities in Indonesia. The multilocation trial is the primary requirement for variety release before farmers can widely use the new varieties. Various stability measurements on grain yields will provide more accurate information in selecting superior lines. The aims of the study were to: (i) identify the effect of genotype by environment interactions (G×E) on black soybean grain yields; (ii) select the black soybean lines with stable and high grain yields in different agroecosystems; and (iii) determine the best representative environment for testing black soybean lines. The field trials used an augmented design that was applied in three blocks for each location. The research was conducted in West Java, Indonesia, specifically in Sumedang, Indramayu, and Majalengka. The three locations are traditionally soybean production areas in West Java. The results showed that G×E significantly affected grain yields, with a contribution of 38.35%. Based on the results of stability testing using parametric, non-parametric, and genotype plus genotype by environments (GGE) biplot measurements, the G13, G22, G25, and G26 lines were considered the most stable and produced the highest yields in the three agroecosystems. In addition, Sumedang is the most representative location for testing black soybeans in Indonesia. Therefore, the four lines can be proposed as new superior lines for black soybeans with high yields and stability in three environments. Information about the relationship between the yield stability parameters can be used for the most accessible parameter selection.

Yield and yield attributes are important components in genotypic evaluation. The butterfly pea is a native plant of Indonesia, and it is considered an underutilized crop. The goals of this study were to evaluate genotypes using environment (year) interactions (GEIs) with yield and yield attributes, and evaluate butterfly pea genotypes based on stability measurements and sustainability index (SI). The study was conducted at the Ciparanje Experimental Field, Faculty of Agriculture, Universitas Padjadjaran using 35 butterfly pea genotypes in a randomized complete block design with two replications. The field trial was conducted over three years (2018–2020). The results showed that the yield and yield attributes were influenced by GEIs. Additive main effects and multiplicative interaction (AMMI) selected 11 stable genotypes (31.43%); genotype plus genotype by environment interaction (GGE) biplot, AMMI stability value (ASV), and genotype stability index (GSI), each selected six genotypes (17.14%) that were stable and high-yielding, and SI selected 18 genotypes (51.43%) that were stable and high-yielding. There were three genotypes identified by all measurements, namely G2, G14, and G16. These three genotypes can be selected as the superior genotypes of the butterfly pea for flower production, and can be used as material for crosses in plant-breeding prog.